The aim of this project is to dramatically improve the quality of immersive social virtual environments (IVEs). By 'quality' we refer to the response of participants to virtual social situations, in particular the extent to which they respond realistically to what they perceive. By 'response' we mean at every measurable level, ranging from non-conscious physiological processes (such as changes in electrodermal activity or heart rate variability) through to overt behavioural, emotional and cognitive responses / including what they report in interviews about their subjective state of mind. By social IVEs we specifically refer to applications where one or more human participants interact with virtual humanoid characters (avatars) in a socially defined context. Specifically, our objectives are to improve the visual appearance of interactive characters and their interactive behaviour especially so that their behaviour responds appropriately to the behaviour of the participants. Third, social IVEs will be constructed that are well-studied in the social psychology literature, and which are of great societal importance, referred to as bystander behaviour in violent emergencies such as in street violence. Finally, these virtual social situations will be used in a series of experimental studies in order to test whether indeed these objectives do improve the quality of response of participants within these social IVEs.One of our goals is to exploit our research in socially useful applications, and thereby also contribute to the growing body of research that uses VEs as a laboratory for social psychological research. In particular we consider the research program of Levine and colleagues at Lancaster on bystander behaviour in violent emergencies. This research program revisits the classic 'bystander effect' in social psychology. The bystander effect suggests that the more witnesses there are to an emergency, the less likely an individual bystander is to intervene. This phenomenon was identified as a consequence of the apparent inaction of 38 witnesses to the brutal rape and murder of Kitty Genovese in New York in 1964. The bystander effect is one of the most robust and reproduced effects in social psychology. However, it lacks practical utility, since for ethical and practical reasons it is not possible to study it scientifically under controlled conditions. In this project we aim to study the bystander effect in the context of virtual environments, where other work has shown that people do tend to respond realistically to virtual social situations.

The aim of this project is to dramatically improve the quality of immersive social virtual environments (IVEs). By 'quality' we refer to the response of participants to virtual social situations, in particular the extent to which they respond realistically to what they perceive. By 'response' we mean at every measurable level, ranging from non-conscious physiological processes (such as changes in electrodermal activity or heart rate variability) through to overt behavioural, emotional and cognitive responses / including what they report in interviews about their subjective state of mind. By social IVEs we specifically refer to applications where one or more human participants interact with virtual humanoid characters (avatars) in a socially defined context. Specifically, our objectives are to improve the visual appearance of interactive characters and their interactive behaviour especially so that their behaviour responds appropriately to the behaviour of the participants. Third, social IVEs will be constructed that are well-studied in the social psychology literature, and which are of great societal importance, referred to as bystander behaviour in violent emergencies such as in street violence. Finally, these virtual social situations will be used in a series of experimental studies in order to test whether indeed these objectives do improve the quality of response of participants within these social IVEs.One of our goals is to exploit our research in socially useful applications, and thereby also contribute to the growing body of research that uses VEs as a laboratory for social psychological research. In particular we consider the research program of Levine and colleagues at Lancaster on bystander behaviour in violent emergencies. This research program revisits the classic 'bystander effect' in social psychology. The bystander effect suggests that the more witnesses there are to an emergency, the less likely an individual bystander is to intervene. This phenomenon was identified as a consequence of the apparent inaction of 38 witnesses to the brutal rape and murder of Kitty Genovese in New York in 1964. The bystander effect is one of the most robust and reproduced effects in social psychology. However, it lacks practical utility, since for ethical and practical reasons it is not possible to study it scientifically under controlled conditions. In this project we aim to study the bystander effect in the context of virtual environments, where other work has shown that people do tend to respond realistically to virtual social situations.

The aim of this project is to dramatically improve the quality of immersive social virtual environments (IVEs). By 'quality' we refer to the response of participants to virtual social situations, in particular the extent to which they respond realistically to what they perceive. By 'response' we mean at every measurable level, ranging from non-conscious physiological processes (such as changes in electrodermal activity or heart rate variability) through to overt behavioural, emotional and cognitive responses / including what they report in interviews about their subjective state of mind. By social IVEs we specifically refer to applications where one or more human participants interact with virtual humanoid characters (avatars) in a socially defined context. Specifically, our objectives are to improve the visual appearance of interactive characters and their interactive behaviour especially so that their behaviour responds appropriately to the behaviour of the participants. Third, social IVEs will be constructed that are well-studied in the social psychology literature, and which are of great societal importance, referred to as bystander behaviour in violent emergencies such as in street violence. Finally, these virtual social situations will be used in a series of experimental studies in order to test whether indeed these objectives do improve the quality of response of participants within these social IVEs.One of our goals is to exploit our research in socially useful applications, and thereby also contribute to the growing body of research that uses VEs as a laboratory for social psychological research. In particular we consider the research program of Levine and colleagues at Lancaster on bystander behaviour in violent emergencies. This research program revisits the classic 'bystander effect' in social psychology. The bystander effect suggests that the more witnesses there are to an emergency, the less likely an individual bystander is to intervene. This phenomenon was identified as a consequence of the apparent inaction of 38 witnesses to the brutal rape and murder of Kitty Genovese in New York in 1964. The bystander effect is one of the most robust and reproduced effects in social psychology. However, it lacks practical utility, since for ethical and practical reasons it is not possible to study it scientifically under controlled conditions. In this project we aim to study the bystander effect in the context of virtual environments, where other work has shown that people do tend to respond realistically to virtual social situations.

Gun crime is a problem in some areas in the UK and many other countries. The police have ways of detecting criminals carrying guns, but this usually involves surveillance over a period of time together with targeted stop and search. There is no affordable detector available that is capable of remotely sensing whether a person is likely to be carrying a gun or not. The police do have scanners and portals that can be installed at key locations such as airports and major event venues to detect people carrying even small metal objects, or portals that use harmless microwaves, THz waves or very low level x-rays to form images of concealed guns on a person. THz and microwaves can form clear body images by penetrating clothing, but moral and technical issues arise from the technology, particularly intrusion into privacy. Also, these are not easily deployable, however, and are still at the research stage in many cases. What is really required is a portable device capable of remotely and discretely detecting whether suspects are carrying weapons and this proposed project aims to commence the development of such a device. During its development, the research will aim to first identify what sort of electromagnetic radiation best penetrates clothing over a range of atmospheric conditions. Microwaves are a form of electromagnetic radiation, but other forms exist such as light, infra-red, Tera-Hertz and millimetre waves and they all differ in their ability to penetrate fabrics. It is also possible to use ultrasound to detect metal objects concealed under clothing and we also propose to investigate this. Some of these forms of electromagnetic radiation get absorbed by the body, whereas others are reflected back depending on the precise wavelength. We will be looking for reflections off the surfaces of the gun in a similar manner to radar detecting the bright echoes from ships and aircraft, whilst filtering out the lower level reflections from the human body. Guns are not the only objects that could be concealed about a person that could give these bright reflections at a remote sensing site. Mobile phones, leather wallets, pens and portable music players could also give detectable signals. We aim to use features unique to a gun, such as gun barrels and other cavities to identify unique signatures in the reflected signals. For example, the gun barrel acts as a resonant cavity rather like air blown over a musical wind instrument, and we aim to detect these resonances remotely. During the second phase of the investigation, we will utilise a mix of the most effective bands in the electromagnetic spectrum, whether that be radio frequencies, microwaves or some other part of the spectrum, together with ultrasound, to develop a sensor that is effective at detecting guns remotely and is deployable by the police. It is possible that different guns will produce different responses from the sensor, but we will use pattern recognition techniques similar to those used in the automatic recognition of number plates or handwriting (i.e. neural networks ) to learn to recognise these particular responses. The research will be undertaken by a consortium of Universities, namely Manchester Metropolitan University, Manchester University, University of Huddersfield and Queen Mary London who will each investigate different aspects of the problem.

Gun crime is a problem in some areas in the UK and many other countries. The police have ways of detecting criminals carrying guns, but this usually involves surveillance over a period of time together with targeted stop and search. There is no affordable detector available that is capable of remotely sensing whether a person is likely to be carrying a gun or not. The police do have scanners and portals that can be installed at key locations such as airports and major event venues to detect people carrying even small metal objects, or portals that use harmless microwaves, THz waves or very low level x-rays to form images of concealed guns on a person. THz and microwaves can form clear body images by penetrating clothing, but moral and technical issues arise from the technology, particularly intrusion into privacy. Also, these are not easily deployable, however, and are still at the research stage in many cases. What is really required is a portable device capable of remotely and discretely detecting whether suspects are carrying weapons and this proposed project aims to commence the development of such a device. During its development, the research will aim to first identify what sort of electromagnetic radiation best penetrates clothing over a range of atmospheric conditions. Microwaves are a form of electromagnetic radiation, but other forms exist such as light, infra-red, Tera-Hertz and millimetre waves and they all differ in their ability to penetrate fabrics. It is also possible to use ultrasound to detect metal objects concealed under clothing and we also propose to investigate this. Some of these forms of electromagnetic radiation get absorbed by the body, whereas others are reflected back depending on the precise wavelength. We will be looking for reflections off the surfaces of the gun in a similar manner to radar detecting the bright echoes from ships and aircraft, whilst filtering out the lower level reflections from the human body. Guns are not the only objects that could be concealed about a person that could give these bright reflections at a remote sensing site. Mobile phones, leather wallets, pens and portable music players could also give detectable signals. We aim to use features unique to a gun, such as gun barrels and other cavities to identify unique signatures in the reflected signals. For example, the gun barrel acts as a resonant cavity rather like air blown over a musical wind instrument, and we aim to detect these resonances remotely. During the second phase of the investigation, we will utilise a mix of the most effective bands in the electromagnetic spectrum, whether that be radio frequencies, microwaves or some other part of the spectrum, together with ultrasound, to develop a sensor that is effective at detecting guns remotely and is deployable by the police. It is possible that different guns will produce different responses from the sensor, but we will use pattern recognition techniques similar to those used in the automatic recognition of number plates or handwriting (i.e. neural networks ) to learn to recognise these particular responses. The research will be undertaken by a consortium of Universities, namely Manchester Metropolitan University, Manchester University, University of Huddersfield and Queen Mary London who will each investigate different aspects of the problem.